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Study On Vegetation Character And Nutrient Elements Dynamics Of Marsh Wetland In North Of Xiaoxing'an Mountain

Posted on:2006-11-11Degree:DoctorType:Dissertation
Country:ChinaCandidate:X L ManFull Text:PDF
GTID:1100360182461547Subject:Ecology
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Mountain marsh wetland mainly distributes at Daxing'an Mountain area and Xiaoxing'an Mountain area in the Northeast of China, it has great effect on adjusting the climate and improving ecosystem. Because of the human's activity, such as peat exploitation, making farmland by draining, damming and minerals exploitation, the area of the wetland shrinks rapidly, and there are unprecedented dangers to the marsh ecosystem of mountain wetlands of Northeast, China. For these reasons, it is an urgent task to undertake the basic research, ecological function and degeneration mechanism on the wetland ecosystem as soon as possible. Taking the marsh of north of the Gongbiela River basin, Xiaoxing'an Mountain as study site, the wetland flora character, the changing rules of nutritional elements and the purifying water quality of marsh wetland are reported in this paper, so as to provide scientific basis for restoration of wetland ecosystem. The mainly results are as follows:(1) There are spermatophyte 44 families 112 genera 164 species in the mire wetland of Gongbiela River basin, the composition of families and genera are fairly rich, but the number of the species are scarce comparatively. The family distribution kind mostly belongs to cosmopolitan north-temperate-zone of the Northern Hemisphere, the genera distribution kind mostly belongs to the temperate zone property, and the species distribution kind mostly belongs to the temperate zone property and the sub-frigid zone to frigid zone property, all in all, the flora character belongs to temperate zone. Simultaneously, the marsh vegetation in this region has the characters of the northeast plant and Daxing'an Mountain plant character, which is the typical intersection ecotope.(2) The distribution of nutritional elements of marsh vegetation of this area shows: N, Ca and Mg mainly concentrated in leaves;P, K and Mn mainly concentrated in spikes;Fe mainly concentrated in roots. The distribution character of Zn and Cu shows no regularity. In herbaceous plants, the concentration of K is the highest, N is the second (Fe in roots), and Zn and Cu are the lowest. In shrubs, the concentration of N is the highest, Ca and K are the second, Zn and Cu are the lowest. From May to September, the concentration of N, P, K and Cu indicate monotonous decreasing trend in leaves, and an increasing trend on the end growing season in roots. The concentration of N, P, K and Cu behavesmonotonous decreasing in the stem of grass (Carex L.), but there little variation in stem of shrub. The content Ca is gradually increasing in the every organisms. There is big seasonal variation in the contents of Mg and Fe, but the Mn and Zn is reverse.(3) The horizontal distribution character of nutritional elements of the mire soil indicates: the concentration of total N, Ca> Mg and Cu are the highest in the plot belt II, and there is decline trend with the altitude rise among all the plot belts. The concentration of total K, P, Fe behave the trend of increasing with altitude in the A layer soil. The concentration of Mn decreases with the increasing distance from away river;the concentration of Zn show less variation among all layers of the plot belt. The average concentration of total K is 1.57% , the highest among the macro-elements(which is absorbed by plant in a great mount relatively), and Fe is 3.05%, the highest among the micro-elements(which is absorbed by plant in a little mount relatively). The overall order is: Fototal K>Mg>Ca>total N>total P> Mn>Zn >Cu.(4) The vertical distribution of nutritional elements in the marsh soil shows : the contents of total N , total P , available K, Ca, Cu and Mn decrease gradually with increasing of the soil depth. The concentration of total K, Mg, Fe gradually increase with the soil depth, however, the change of concentrations of Mg, Fe and Zn are unapparent between different soil layers. The contents change of total Pn Ca, Fe and Mn behave obvious single peak curve with the season, and the peak point appears in June or July;Mg change less;the contents change of total K present double curves in the A layer soil, upper in June and August, contents change available K show decline in the A layer soil from May to August. Contents change of N, Cu and Zn fluctuate seasonally.(5 ) In the area, the dominant negative ion is HCO3" in the representative wetland water, the dominant positive ion is Ca2+, so the hydrochemical type is bicarbonate kind, calcium section type I (CiCa), the concentration of total hardness> HCO3", SO42~, Ca, Na, Mg, Mn and Fe decrease gradually along with the distance rise from away the river. The changing extent of PH and CF is less in the all 3 types wetlands. The concentration of N, Na+ and Cl" rise undulatingly from May to September, K+ occurs double peak curve in May and August, respectively. The contents changes of total P, Fe and Mn indicate single peak curve in the water of 2 types wetlands, in which grow Sanguisorba parviflora and Salix rosmarinifolia-Carex schmidtii, the maximum occurs July, and Ca2+, HCO3" display undulating rising trend in the water of wetlands, in which grow Betula fruticosa-Aulacomnicum palustre, the concentrations of total P, Fe and SO42' ar;the highest in August, but Ca2+, Mg2+and Mn show less variation.(6) The content of total ion number, mineralization of water, total rigidity, totalalkalinity > HCC>3\ SC>42\ Ca2+> Mg2+and Fe in the forest rivulet are all below that in the river by wetland, but Cl\ K+, Na+, Mn^ total N and total P contents are reverse. So, for improving water quality, both forest and wetland are important, the difference is that forest and wetland decontaminating pollutant, for instance, the forest has a stronger decontaminative effect on Ca^ MgandFe, however, the wetland on N, P.
Keywords/Search Tags:Mountain marsh wetland, vegetation character, nutritional elements, hydrochemistry, seasonal dynamics
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